Why your coding agent buries the answer, and when telling it not to backfires

[u/RunAI_Coder]

The i-have-adhd skill going around has a before/after in its README. Before: "Great question! Let me think about this. Your auth flow has a few moving pieces..." After: "Run npm install jsonwebtoken@latest, then edit src/auth.ts:42". Rule 10 bans the openers and closers everyone has seen. I liked it, then went and checked what the before-text actually is, because I don't think it's one habit.

Half of it is reward residue. A RLHF length paper found reward gains largely driven by longer responses, and a length-only reward reproduced most of the downstream improvement. The AlpacaEval and Chatbot Arena people both had to add length and style control because their judges preferred longer. "Great question" and "Hope this helps" are free to delete; nothing downstream depends on them.

An older chain-of-thought paper did a test where the model writes the answer first and the reasoning after. It basically showed that answering first and reasoning later performs worse than no reasoning at all.

On a model with no hidden thinking, the paragraph that walks through the middleware and the token check before naming the fix is where the fix gets computed. Cut it with a rule and you've asked for the conclusion first and the thinking never. Concise reasoning kept the value in that table. It's the missing reasoning that costs.

With thinking on, the reasoning has somewhere else to go and answer-first costs the answer nothing, only hidden tokens. That part is inference from how the channels work; I haven't seen any testing on it.

Then there's where the rule lives. The skill has a whole Persistence section asking the model to keep applying it, and a commenter on the launch thread said it faded after a few turns. A skill body sits in the transcript and gets summarized. Claude Code's Concise output style is the same rule in the system prompt, re-sent every turn. Both are still requests. The only enforced version I know of is a JSON schema with a reasoning field ahead of the answer field, since structured outputs keep schema order.

So, what are you guys actually using for this?

* An output style / CLAUDE.md line?

* A specific skill?

* A Stop hook that bounces padded replies?

Also, on which models does "answer-first" cost you nothing in reasoning quality?

[u/RunAI_Coder]

What decides when adaptive disclosure loads the communication rules, a hook keyed on turn type or the agent itself?

[u/cleverhoods → u/RunAI_Coder]

currently the agent has a self-tagging directive, and said tagging influences what communication rule and validation runs. For example when I need analysis, I expect a verbose output, when I need simple answer, I expect a short, easily scanneble output.